Algorithmic Talent Management: A Literature Review on the Usage and Impact of Artificial Intelligence in Human Resource Management

Abstract

This study presents a systematic literature review examining the integration, usage, and implications of Artificial Intelligence (AI) within Human Resource Management (HRM). As organizations encounter intensifying global competition and escalating data volumes, traditional administrative personnel workflows are rapidly transitioning toward algorithmic talent acquisition, automated performance tracking, and predictive retention analytics. By synthesizing contemporary peer-reviewed literature and applying established management theories—such as the Resource-Based View (RBV), Dynamic Capabilities Theory, and Person-Organization Fit Framework—this paper maps how AI transforms key HR architecture. The review demonstrates that while AI applications substantially accelerate recruitment cycles, reduce administrative burdens, and enhance objective decision-making, they simultaneously introduce critical challenges, including algorithmic bias, data privacy vulnerabilities, loss of human empathy, and employee resistance. Finally, this review highlights prominent research gaps and delivers strategic recommendations for organizational leaders and human resource practitioners navigating intelligent automation.